Towards Graph Summary and Aggregation: A Survey

  • Jinguo YouEmail author
  • Qiuping Pan
  • Wei Shi
  • Zhipeng Zhang
  • Jianhua Hu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 387)


To obtain the insight in a single large graph and to save the space consumption for graph mining, the graph summary transforms the input graph into an aggregated concise super-graph represented by supernodes and superedges. In this paper, we investigate current algorithms of the graph summary and aggregation. We provide the classification of them in terms of partition criterion or information lossless. Further, the main graph summary algorithms are compared and discussed in detail. In the end, we give the challenges and future works.


Graphs Networks Summarization Aggregation 



This work is supported by the Natural Science Foundation of Yunnan Province, China (2010ZC030) and is partially done when the author(s) visited Sa-Shixuan International Research Centre for Big Data Management and Analytics hosted in Renmin University of China. This Center is partially funded by a Chinese National “111” Project “Attracting International Talents in Data Engineering and Knowledge Engineering Research”.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jinguo You
    • 1
    Email author
  • Qiuping Pan
    • 1
  • Wei Shi
    • 2
  • Zhipeng Zhang
    • 1
  • Jianhua Hu
    • 1
  1. 1.School of Information Engineering and AutomationKunming University of Science and TechnologyKunmingChina
  2. 2.Department of ComputerXidian UniversityXi’anChina

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